Crop Recommendation System

This research project presents a Crop Recommendation System. The system leverages Machine Learning algorithms to assist farmers in making informed decisions about crop selection. By analyzing environmental parameters such as soil nutrients (Nitrogen, Phosphorous, Potassium), temperature, humidity, and rainfall, the model predicts the most suitable crop to maximize yield and promote sustainable agricultural practices.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-27
DOI
https://doi.org/10.5281/zenodo.19811799
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
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article

Crop Recommendation System

Pratik Patil, Rohan Dagade, Parth Kerale, Rudra Bade
Zenodo (CERN European Organization for Nuclear Research)
Smart Agriculture and AI
article

Crop Recommendation System

Pratik Patil, Rohan Dagade, Parth Kerale, Rudra Bade
article en

Abstract

This research project presents a Crop Recommendation System. The system leverages Machine Learning algorithms to assist farmers in making informed decisions about crop selection. By analyzing environmental parameters such as soil nutrients (Nitrogen, Phosphorous, Potassium), temperature, humidity, and rainfall, the model predicts the most suitable crop to maximize yield and promote sustainable agricultural practices.

Zenodo (CERN European Organization for Nuclear Research)
MIT Art, Design and Technology University (IN)
Zero hunger
Openalex Percentile: Top 6%
Smart Agriculture and AI
DOIOpen Access PDFOpenAlex
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Crop Recommendation System — Pratik Patil, Rohan Dagade, et al. · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS